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编者按：市场化利率的发展将会促使商业银行的收入结构发生变化，亦将改变商业银行的资产负债管理体系。商业银行在面对利率市场化改革时，需如何应对资产负债管理中出现的问题，需要有新思考与新对策。
Robert J. Wyle，穆迪公司产品管理部高级总监，ALM领域资深专家。不久前，Robert应邀在金融咨询网开设专栏并将陆续发布与ALM相关的一些观点文章及研究成果。金融咨询网将以“中文简介+英文原文”的方式刊发这些专栏文章。
文章概要：这篇文章对过往很多企业的CEO或者董事局曾经用来评测利率风险对资本和收益的影响的分析工具进行了介绍和评价。同时，作者亦尝试分析2007年末的金融风暴所带来的教训，并探讨了在此之后发展的新兴金融风险管理理念。过往大部分银行都比较积极监控结构性的资产与负债风险，但是，不像市场风险和信用风险，市场上对资产负债风险还没有一套标准的衡量指标。
实际上，大部分的业内人士连利率风险指标是否应该基于收益敏感性、市场价值敏感性或者传统的现金流缺口模型都没有共识。在这种情况下，也不难理解为什么资产负债管理的实践五花八门，而且各有复杂性。因此，没有一个ALM风险管理工具是理想的，我们见到的都各有优劣。所以，要有效管理资产负债表，金融机构必须要考虑在快速变化的监管环境下如何选择适合自身规模和复杂性的风险管理目标的工具。全球的监管机构普遍认为ALM本身是不足够的，并在强迫金融机构进一步加强其风险管理的实践。
以下为英文原文。
An Evaluation of Interest Rate Risk Tools and the Future of Asset Liability Management
Abstract
This paper identiies, describes, and evaluates the analytical tools that CEOs and corporate boards have used to understand capital and earnings exposure to interest rate risk. Furthermore, the paper examines lessons learned as a result of the market turbulence that began in late 2007 and explores how the nature of inancial risk management is evolving. Most banks actively monitor structural asset and liability risk; however, unlike market or credit risk, there are no standard metrics to assess asset and liability risk. In fact, practitioners do not even agree on whether interest rate risk metrics should be based on earnings sensitivity, market value sensitivity, or the traditional cash low gap model. Given this lack of consensus and standardization, it is not surprising that there is a wide range of Asset Liability Management (ALM) practices and sophistication. Moreover, while no ALM risk management tool is ideal, each has its strengths and weaknesses. To effectively manage their balance sheet, inancial institutions must select the risk management tools that are appropriate for the institution’s size, complexity and risk management objectives in the context of a dynamic regulatory environment. The global regulatory community has indicated that ALM was not adequate and is forcing banks to improve their risk management practices.
1. Introduction
ALM is deined in several ways. Traditionally, ALM has been associated with the management of structural balance sheet interest rate risk (IRR). The traditional deinition of IRR is “the exposure of a bank’s inancial condition to adverse movements in interest rates”. This deinition, however, considers only a single risk factor. Consistent with this deinition, the tools for measuring and monitoring IRR have historically been the Repricing Gap Model, net Interest Income (nII) simulation, and the sensitivity of Market Value of Portfolio Equity. At some banks, due to the concentration of skills and cash low models, the ALM function is also responsible for performing a variety of other balance sheet management analyses including:
>> Liquidity Risk
>> Funds Transfer Pricing (FTP)
>> Capital Management
>> Risk Policy setting
Therefore, depending on the institution, the full scope of ALM can be much broader than just IRR. And given the lack of standardization in the industry, it is not surprising that there is a wide range of sophistication in ALM.
Approaches to ALM can be broadly categorized as simple or sophisticated:
simpler approaches to ALM
>> Periodic Gap Model
>> Calculating the impact of parallel and instantaneous interest rate shocks on static earnings or market value using discounted cash low analysis.
Sophisticated approaches to ALM
>> Dynamic simulation of the balance sheet under multiple interest rate scenarios
>> Option Adjusted Valuation (OAV) Volatility-based risk metrics that include Value at Risk (VaR), stochastic Earnings at Risk (EaR), Risk Adjusted Return on Capital (RAROC), or Economic Value Added (EVA)
While regulators and practitioners might agree on what ALM risk management tools are available, they do not necessarily agree on which ALM tools should be used to quantify risk (that is, an earnings-based sensitivity or market value sensitivity.) Regulators are demanding stronger risk management practices and so banks are increasingly looking at more sophisticated approaches to ALM. This lack of consensus on how to measure ALM risk was a major reason why interest rate risk outside the trading book was not subjected to an explicit (Pillar 1) capital charge under Basel II but is covered under Pillar 2 instead (BCBs 2005, §762).
Lessons Learned
The industry and regulatory response to the market dislocations that began in late 2007 have sparked renewed interest in ALM. Traditional approaches to ALM did not foresee or prevent the credit crisis. Some of the key lessons learned include:
>> The need for effective irm-wide risk identiication and analysis: Firms that were better able to share quantitative and qualitative information across the enterprise were better able to identify the sources for inherent risks sooner. These irms identiied risks earlier which gave them more time to develop irm-wide solutions rather than wait and hope that the lines would make decisions that beneit theirm’s exposures collectively. Firms that performed less well did not effectively share information, and the lines were left to make decisions in isolation.
>> The consistent application of independent and rigorous valuation practices across the irm: Firms that performed better throughout the credit crisis generally had a more disciplined enterprise valuation process. These irms developed in-house infrastructure and governance capability to quantify and share the intrinsic value of complex potentially illiquid securities. These irms identiied future risks sooner and had more time to frame enterprise risk management strategies.
>> The effective management of funding, liquidity, capital, and the balance sheet: Firms that implemented and enforced enterprise risk management control systems for the management of capital and liquidity tended to perform better during the credit crisis. For example, irms that aligned their Treasury functions more closely with risk management processes provided internal incentives for individual business lines to control activities that might lead to unexpected losses primarily by charging the business lines for contingent liquidity risk.
>> informative and responsive risk measurement and management reporting and practices: Better performing irms tended to look at risk using metrics that were based on different underlying assumptions and were better able to update their modeling assumptions to better relect current market conditions. These irms were better able to evaluate forward-looking scenarios under changing market circumstances and pursue opportunities as they emerged. In contrast, irms that experienced more dificulty were dependent on speciic risk measures which might have been based on outdated information.